Search Results for author: Mark Iwen

Found 2 papers, 0 papers with code

Neural Network Approximation of Continuous Functions in High Dimensions with Applications to Inverse Problems

no code implementations28 Aug 2022 Santhosh Karnik, Rongrong Wang, Mark Iwen

The approach is based on the observation that the existence of a Johnson-Lindenstrauss embedding $A\in\mathbb{R}^{d\times D}$ of a given high-dimensional set $S\subset\mathbb{R}^D$ into a low dimensional cube $[-M, M]^d$ implies that for any H\"older (or uniformly) continuous function $f:S\to\mathbb{R}^p$, there exists a H\"older (or uniformly) continuous function $g:[-M, M]^d\to\mathbb{R}^p$ such that $g(Ax)=f(x)$ for all $x\in S$.

A Hybrid Scattering Transform for Signals with Isolated Singularities

no code implementations10 Oct 2021 Michael Perlmutter, Jieqian He, Mark Iwen, Matthew Hirn

We also show that the Gabor measurements used in the second layer can be used to synthesize sparse signals such as those produced by the first layer.

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